One aspect of Automated Reasoning (AR) deals with writing computer programs that can answer questions using logical reasoning. An Automated Theorem Proving system (ATP system) translates a question to be answered to a first-order logic conjecture, and attempts to prove the conjecture from a set of axioms provided, thereby leading to a proof. If a proof is found an answer extraction method can be applied to answer the original question. If more than one proof is possible, more than one answer may need to be extracted. For ATP systems that can find only one answer at a time, to answer questions that yield multiple answers, the ATP system can be re-invoked with a modified question to find other possible answers. In this thesis, an answer extraction method has been designed to extract more than one answer when an ATP system is used to answer a question that has multiple answers. The method is implemented in an interactive computer program and the process is called multiple-answer extraction. The answer extraction software, called the multi-answer system, is a three layered software architecture model. SNARK, at the bottom-most layer, serves as the ATP system that finds single answers. The answer extractor, in the middle layer, extracts possible answers by re-invoking the ATP system. The top layer compares the answers extracted to the user's expected answers. The software is command line driven. Keywords such as all, some, n (where n is a number), while and until are specified on the command line to limit the number of answers to be extracted. The top layer allows the user to check properties of the answer, e.g., if a specific element belongs to the set of answers obtained, or if the user's set of answers is a subset of the answers returned by the multi-answer system. This is done using set operations, such as subset, element of, union, difference, intersection, on the user's set of answers and the extracted set of answers.

Automated reasoning, and in particular automated theorem proving, has become a very important research field within the world of mathematics. Besides being used to verify proofs of theorems, it has also been used to discover proofs of theorems which were previously open problems. In this thesis, an automated reasoning assistant based on Godel's class theory is used to deduce several theorems.

Published Article / RFID can work in conjunction with sensors in material handling especially on a conveyor belt. A dozen different graded tagged products can be picked up by the RFID system in real-time and transported to respective chutes into automatic guided vehicles (AGV) for transportation to specific storage locations. The development of this system is now at an advanced stage. Our predictions to date show that the application of RFID in material handling in a manufacturing environment can assist in the fast flow of components throughout the assembly line beyond what available systems can do.

International Telemetering Conference Proceedings / October 26-29, 1998 / Town & Country Resort Hotel and Convention Center, San Diego, California / The recent proliferation of Low Earth Orbiting (LEO) science, earth resources, and global communication satellites requires a significant number of ground stations for support. A network of satellite tracking ground stations with the ability to support multiple users and communicate with multiple satellites requires a robust scheduling and conflict resolution system. This paper describes an automated scheduling implementation for managing such a commercial, multi-user, multiple satellite, ground station network.

Many tasks require surveillance and analysis in order to make decisions regarding the next course of action. The people responsible for these tasks are usually concerned with any event that affects their bottom-line. Traditionally, human operators have had to either actively man a set of video displays to determine if specific events were occurring or manually review hours of collected video data to see if a specific event occurred. Actively monitoring video stream or manually reviewing and analyzing the data collected, however, is a tedious and long process which is prone to errors due to biases and inattention. Automatically processing and analyzing the video provides an alternate way of getting more accurate results because it can reduce the likelihood of missing important events and the human factors that lead to decreased efficiency. The thesis aims to contribute to the area of using computer vision as a decision support tool by integrating detector, tracker, re-identification, activity status estimation, and event processor modules to generate the necessary event statistics needed by a human operator. The contribution of this thesis is a system that uses feedback from each of the modules to provide better target detection, and tracking results for event statistics generation over an extended period of time. To demonstrate the efficacy of the proposed system, it is first used to generate event statistics that measure productivity on multiple construction work sites. The versatility of the proposed system is also demonstrated in an indoor assisted living environment by using it to determine how much of an influence a technology intervention had on promoting interactions amongst older adults in a shared space.

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